How to use PyTorch for Deep Learning with Python? – Mastering PyTorch

PyTorch Basics

Neural Network Components

Loss functions

  • How to use Huber Loss with PyTorch?
  • How to use Hinge & Squared Hinge Loss with PyTorch?
  • How to use Categorical / Multiclass Hinge with PyTorch?
  • How to use Binary & Categorical Crossentropy with PyTorch?
  • How to use Sparse Categorical Crossentropy with PyTorch?
  • How to use MAE, MSE, MAPE & RMSE with PyTorch?
  • How to use Logcosh with PyTorch?
  • How to use Kullback-Leibler divergence (KL divergence) with PyTorch?

Normalization & regularization

  • How to use Batch Normalization with PyTorch?
  • How to use L1, L2 and Elastic Net Regularization with PyTorch?
  • How to use Dropout with PyTorch?

Convolutional Neural Networks

  • How to create a Convolutional Neural Network classifier with PyTorch?
  • How to use 2D Conv layers with PyTorch?
  • Implementing depthwise separable convolutions with PyTorch
  • Handling 3D data with PyTorch
  • Performing transposed convolutions with PyTorch
  • Upsampling your ConvNet data with PyTorch
  • Cropping inputs to ConvNets with Pytorch
  • How to use padding with PyTorch?
  • Using Constant Padding, Reflection Padding and Replication Padding with PyTorch
  • Max Pooling, Average Pooling, Global Max Pooling, Global Average Pooling – PyTorch examples
  • How to build a ConvNet for CIFAR-10 and CIFAR-100 classification with PyTorch?

Data preprocessing

Model evaluation

Advanced topics

Datasets

  • Working with Imbalanced Datasets with PyTorch
  • Exploring the PyTorch datasets

Neural Networks

  • Creating a Multilabel Neural Network Classifier with PyTorch

Model visualization

  • Coming soon.